Unsupervised Anomaly Detection

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

18 leaderboard tables shown for this task, 18 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted. 10 shown of 18 until expanded.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

27 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

5 subtasks in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 226 papers with code (506 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level Latencies
  25 Mar 2023 33 repositories listed Syntology ran 1 of 35 samples · 34 unverified
  We train a student network to predict the extracted features of normal, i.
• Glow: Generative Flow with Invertible 1x1 Convolutions
  9 Jul 2018 27 repositories listed Syntology ran 75 of 129 samples · 54 unverified · 44 pointer-only (licence)
  Flow-based generative models (Dinh et al., 2014) are conceptually attractive due to tractability of the exact log-likelihood, tractability of exact latent-variable inference, and parallelizability of both training and…
• PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization
  17 Nov 2020 26 repositories listed Syntology ran 7 of 7 samples · 0 unverified · 3 pointer-only (licence)
  We present a new framework for Patch Distribution Modeling, PaDiM, to concurrently detect and localize anomalies in images in a one-class learning setting.
• Towards Total Recall in Industrial Anomaly Detection
  15 Jun 2021 18 repositories listed Syntology ran 5 of 36 samples · 31 unverified
  Being able to spot defective parts is a critical component in large-scale industrial manufacturing.
• Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery
  17 Mar 2017 18 repositories listed Syntology ran 3 of 11 samples · 8 unverified · 3 pointer-only (licence)
  Obtaining models that capture imaging markers relevant for disease progression and treatment monitoring is challenging.
• Student-Teacher Feature Pyramid Matching for Anomaly Detection
  7 Mar 2021 10 repositories listed
  Anomaly detection is a challenging task and usually formulated as an one-class learning problem for the unexpectedness of anomalies.
• Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications
  12 Feb 2018 10 repositories listed
  To ensure undisrupted business, large Internet companies need to closely monitor various KPIs (e.
• Anomaly Detection via Reverse Distillation from One-Class Embedding
  26 Jan 2022 5 repositories listed Syntology ran 14 of 18 samples · 4 unverified · 15 pointer-only (licence)
  Knowledge distillation (KD) achieves promising results on the challenging problem of unsupervised anomaly detection (AD).
• FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows
  15 Nov 2021 5 repositories listed Syntology ran 0 of 6 samples · 6 unverified
  However, current methods can not effectively map image features to a tractable base distribution and ignore the relationship between local and global features which are important to identify anomalies.
• TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks
  16 Sep 2020 5 repositories listed
  However, detecting anomalies in time series data is particularly challenging due to the vague definition of anomalies and said data's frequent lack of labels and highly complex temporal correlations.
• Sub-Image Anomaly Detection with Deep Pyramid Correspondences
  5 May 2020 5 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  Nearest neighbor (kNN) methods utilizing deep pre-trained features exhibit very strong anomaly detection performance when applied to entire images.
• Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection
  4 Apr 2019 5 repositories listed Syntology ran 1 of 9 samples · 8 unverified
  At the test stage, the learned memory will be fixed, and the reconstruction is obtained from a few selected memory records of the normal data.
• A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data
  20 Nov 2018 5 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  Subsequently, given the signature matrices, a convolutional encoder is employed to encode the inter-sensor (time series) correlations and an attention based Convolutional Long-Short Term Memory (ConvLSTM) network is…
• Band selection with Higher Order Multivariate Cumulants for small target detection in hyperspectral images
  10 Aug 2018 5 repositories listed
  In this paper we present an analysis of a general algorithm for band selection based on higher order cumulants.
• Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series
  16 Feb 2022 4 repositories listed Syntology ran 8 of 24 samples · 16 unverified · 10 pointer-only (licence)
  Anomaly detection is a widely studied task for a broad variety of data types; among them, multiple time series appear frequently in applications, including for example, power grids and traffic networks.
• TS2Vec: Towards Universal Representation of Time Series
  19 Jun 2021 4 repositories listed Syntology ran 11 of 23 samples · 12 unverified
  Furthermore, to obtain the representation of an arbitrary sub-sequence in the time series, we can apply a simple aggregation over the representations of corresponding timestamps.
• Probabilistic Autoencoder
  9 Jun 2020 4 repositories listed Syntology ran 1 of 13 samples · 12 unverified
  The PAE is fast and easy to train and achieves small reconstruction errors, high sample quality, and good performance in downstream tasks.
• Deep Weakly-supervised Anomaly Detection
  30 Oct 2019 4 repositories listed Syntology ran 5 of 6 samples · 1 unverified
  To detect both seen and unseen anomalies, we introduce a novel deep weakly-supervised approach, namely Pairwise Relation prediction Network (PReNet), that learns pairwise relation features and anomaly scores by…
• Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty
  28 Jun 2019 4 repositories listed Syntology ran 5 of 12 samples · 7 unverified
  Self-supervision provides effective representations for downstream tasks without requiring labels.
• DeepAnT: A Deep Learning Approach for Unsupervised Anomaly Detection in Time Series
  19 Dec 2018 4 repositories listed
  In contrast to the anomaly detection methods where anomalies are learned, DeepAnT uses unlabeled data to capture and learn the data distribution that is used to forecast the normal behavior of a time series.
• MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection
  9 Apr 2024 3 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  Recent advancements in anomaly detection have seen the efficacy of CNN- and transformer-based approaches.
• Guided Reconstruction with Conditioned Diffusion Models for Unsupervised Anomaly Detection in Brain MRIs
  7 Dec 2023 3 repositories listed
  We demonstrate that this conditioning allows for accurate and local adaptation to the general input intensity distribution while avoiding the replication of unhealthy structures.
• Estimating the Contamination Factor's Distribution in Unsupervised Anomaly Detection
  19 Oct 2022 3 repositories listed Syntology ran 0 of 4 samples · 4 unverified
  We leverage on outputs of several anomaly detectors as a representation that already captures the basic notion of anomalousness and estimate the contamination using a specific mixture formulation.
• DRAEM -- A discriminatively trained reconstruction embedding for surface anomaly detection
  17 Aug 2021 3 repositories listed Syntology ran 2 of 7 samples · 5 unverified
  Visual surface anomaly detection aims to detect local image regions that significantly deviate from normal appearance.
• CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flows
  27 Jul 2021 3 repositories listed Syntology ran 3 of 12 samples · 9 unverified
  Our approach results in a computationally and memory-efficient model: CFLOW-AD is faster and smaller by a factor of 10x than prior state-of-the-art with the same input setting.
• Semi-orthogonal Embedding for Efficient Unsupervised Anomaly Segmentation
  31 May 2021 3 repositories listed
  We present the efficiency of semi-orthogonal embedding for unsupervised anomaly segmentation.
• Uninformed Students: Student-Teacher Anomaly Detection with Discriminative Latent Embeddings
  6 Nov 2019 3 repositories listed Syntology ran 8 of 8 samples · 0 unverified · 3 pointer-only (licence)
  Our experiments demonstrate improvements over state-of-the-art methods on a number of real-world datasets, including the recently introduced MVTec Anomaly Detection dataset that was specifically designed to benchmark…
• f-AnoGAN: Fast Unsupervised Anomaly Detection with Generative Adversarial Networks
  30 Jan 2019 3 repositories listed
  While supervised learning yields good results if expert labeled training data is available, the visual variability, and thus the vocabulary of findings, we can detect and exploit, is limited to the annotated lesions.
• A Unified Anomaly Synthesis Strategy with Gradient Ascent for Industrial Anomaly Detection and Localization
  12 Jul 2024 2 repositories listed Syntology ran 5 of 8 samples · 3 unverified
  Anomaly synthesis strategies can effectively enhance unsupervised anomaly detection.
• Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection
  23 May 2024 2 repositories listed Syntology ran 9 of 10 samples · 1 unverified
  Recent studies highlighted a practical setting of unsupervised anomaly detection (UAD) that builds a unified model for multi-class images.

Syntology lines on 22 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.